The predictive value of TNF family for pulmonary tuberculosis: a pooled causal effect analysis of multiple datasets
Frontiers in Immunology, 2024
Mo W., Cui Z., Zhao J., Xian X., Huang M., Liu J.
| Disease area | Application area | Sample type | Products |
|---|---|---|---|
Infectious Diseases | Pathophysiology | Plasma |  Olink Target 96 |
Abstract
Objective
Despite extensive research on the relationship between pulmonary tuberculosis (PTB) and inflammatory factors, more robust causal evidence has yet to emerge. Therefore, this study aims to screen for inflammatory proteins that may contribute to the susceptibility to PTB in different populations and to explain the diversity of inflammatory and immune mechanisms of PTB in different ethnicity.
Methods
The inverse variance weighted (IVW) model of a two-sample Mendelian Randomization (MR) study was employed to conduct causal analysis on data from a genome-wide association study (GWAS). This cohort consisting PTB GWAS datasets from two European and two East Asian populations, as well as 91 human inflammatory proteins collected from 14,824 participants. Colocalization analysis aimed to determine whether the input inflammatory protein and PTB shared the same causal single nucleotide polymorphisms (SNPs) variation within the fixed region, thereby enhancing the robustness of the MR Analysis. Meta-analyses were utilized to evaluate the combined causal effects among different datasets.
Results
In this study, we observed a significant negative correlation between tumor necrosis factor-beta levels (The alternative we employ is Lymphotoxin-alpha, commonly referred to as LT) (P < 0.05) and tumor necrosis factor receptor superfamily member 9 levels (TNFRSF9) (P < 0.05). These two inflammatory proteins were crucial protective factors against PTB. Additionally, there was a significant positive correlation found between interleukin-20 receptor subunit alpha levels (IL20Ra) (P < 0.05), which may elevate the risk of PTB. Colocalization analysis revealed that there was no overlap in the causal variation between LT and PTB SNPs. A meta-analysis further confirmed the significant combined effect of LT, TNFRSF9, and IL20Ra in East Asian populations (P < 0.05).
Conclusions
Levels of specific inflammatory proteins may play a crucial role in triggering an immune response to PTB. Altered levels of LT and TNFRSF9 have the potential to serve as predictive markers for PTB development, necessitating further clinical validation in real-world settings to ascertain the impact of these inflammatory proteins on PTB.